Analysis of LMS Implementation Success Based on Information System Success and End-User Computing Satisfaction Models by Rahmat Pambudi, Berlilana Berlilana, Giat Karyono

“…A learning Management System (LMS) is critical because it can help improve learning quality and efficiency. …”
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Data-Driven Energy Consumption Analysis and Prediction of Real-World Electric Vehicles at Low Temperatures: A Case Study Under Dynamic Driving Cycles by Yifei Zhao, Hang Liu, Jinsong Li, Hongli Liu, Bin Li

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Research on AGV Path Planning Based on Improved DQN Algorithm by Qian Xiao, Tengteng Pan, Kexin Wang, Shuoming Cui

“…Then, a refined multi-objective reward function is designed, combined with direction guidance, step punishment, and end point reward, to effectively guide the agent in learning an efficient path. …”
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PREDICT: a method for inferring novel drug indications with application to personalized medicine by Assaf Gottlieb, Gideon Y Stein, Eytan Ruppin, Roded Sharan

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A Guidance Framework for Resolving Problems of Credit Card Churn Detection Systems by Fehim Altınışık, Ahmet Sayar

“…The framework used in this study is believed to be used not only in the integration of credit card product churn detection systems but also in the integration of other systems that use machine learning and deep learning.…”
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Teachers’ preparedness for implementing the Educational Coding and Robotics curriculum in South Africa by William Zivanayi, Serah Ntombikayise Malinga

“… It is a significant step that the Department of Basic Education has taken to integrate educational coding and robotics into the mainstream school curricula in a world where technology is a normal element of everyday life. …”
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PROJECT-BASED BUSINESS MANAGEMENT TRAINING FOR WOMEN'S ENTREPRENEURIAL SKILLS DEVELOPMENT by Sri Nurhayati, Farida Arianti Handayani

“…This study explores the implementation and effectiveness of Project-Based Learning (PjBL) in a business management training program for women entrepreneurs at An Nur Ibun Community Learning Center. …”
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The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis by Hatice Kabaoğlu, Emine Uçar, Fecir Duran

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Ensembles of Gradient Boosting Recurrent Neural Network for Time Series Data Prediction by Shiqing Sang, Fangfang Qu, Pengcheng Nie

“…Meanwhile, for ensuring the ensemble model fit data better, Step Iteration Algorithm is designed to find an appropriate learning rate before models being integrated. …”
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PGBTR: a powerful and general method for inferring bacterial transcriptional regulatory networks by Wei-Cheng Gu, Bin-Guang Ma

“…PGBTR consists of two main components: the input generation step PDGD (Probability Distribution and Graph Distance) and the deep learning model CNNBTR (Convolutional Neural Networks for Bacterial Transcriptional Regulation inference). …”
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xLSTMKT: xLSTM for Knowledge Tracing by Yasser Aderghal, Hakim Hafidi, Abdellatif El Ghazi

“…However, existing methods fuse question-specific and knowledge concepts-specific information at an early stage, limiting the model’s ability to fully capture the fine-grained details of student learning dynamics. To address these limitations, we propose a novel framework called xLSTM Knowledge Tracing (xLSTMKT), that explicitly separates student interactions into question-level and skill-level streams, generating dynamic embeddings for each at every time step. …”
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Research on prediction of surrounding rock deformation and optimization of construction parameters of high ground stress tunnel based on WOA-LSTM by Jianquan Yao, Jiajia Nie, Chaofeng Li

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Unsupervised feature selection and class labeling for credit card fraud by Robert K. L. Kennedy, Flavio Villanustre, Taghi M. Khoshgoftaar

“…Results also show that the generated labels, both with and without a feature selection preprocessing step, outperform Isolation Forest (IF), an unsupervised anomaly detection method used as a baseline. …”
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A systematic review of literature reviews on artificial intelligence in education (AIED): a roadmap to a future research agenda by Muhammad Yasir Mustafa, Ahmed Tlili, Georgios Lampropoulos, Ronghuai Huang, Petar Jandrić, Jialu Zhao, Soheil Salha, Lin Xu, Santosh Panda, Kinshuk, Sonsoles López-Pernas, Mohammed Saqr

“…To address this research gap, this study proceeds one step forward by systematically meta-synthesizing the AIED literature reviews. …”
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PointNet++SAKS: A Point Cloud Model Based on KANs and Attention Mechanism for Objects Classification and Semantic Segmentation by Xiaofeng Lu, Zhiwei Guan, Dangfeng Pang, Rupeng Dou, Xiaolong Zheng

“…The introduced SegNext combines Transformer and Convolutional Neural Network (CNN) to extract features from different scales using convolutional kernels of different sizes or convolutional operations with different step sizes. On the Sydney Urban Objects Dataset classification, overall accuracy (OA) and mean accuracy (mAcc) metrics improved by 4.89% and 9.47%, respectively. …”
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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography by Barbara Stefaniak, Tomasz Rymarczyk, Dariusz Wójcik, Marta Cholewa-Wiktor, Tomasz Cieplak, Zbigniew Orzeł, Janusz Gudowski, Ewa Golec, Michał Oleszek, Marcin Kowalski

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Localization of mobile robot in prior 3D LiDAR maps using stereo image sequence by I.V. Belkin, A.A. Abramenko, V.D. Bezuglyi, D.A. Yudin

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Vision Transformers (ViTs) for Feature Extraction and Classification of AI-Generated Visual Designs by Qing Yun

“…Deep learning has become a cornerstone of modern Artificial Intelligence (AI), enabling machines to process and interpret complex visual information with unprecedented accuracy. …”
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Chameleon: A Dataset for Segmenting and Attacking Obfuscated Power Traces in Side-Channel Analysis by Davide Galli, Giuseppe Chiari, Davide Zoni

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Extreme outage prediction in power systems using a new deep generative Informer model by Razieh Rastgoo, Nima Amjady, Syed Islam, Innocent Kamwa, S.M. Muyeen

“…This paper proposes a deep learning-based framework for power data rebalancing and outage prediction in power systems to cope with the extreme events. …”
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